draft, under review for InfoVis '06

The Rhythms of Salience:
A Conversation Map

Judith S. Donath
The Sociable Media Group, MIT Media Lab


Visualizing online conversation archives can reveal useful social patterns. This paper discusses design principles for social visualizations and describes one such design in depth.



Why visualize conversations?

In the face to face world, the information we gather in a conversation comes from the postures, glances, expressions, entrances and exits of the participants, as well as the words they exchange. In the online world of text-based interaction, these sensory cues to the social dynamics are missing. The dynamics are there, but they are hard to perceive.


Visualizing a conversation makes it possible to see these dynamics. While the archives of written conversations cannot provide such cues as the fleeting expressions on a listener's face, they do contain a rich, though different, collection of contextual data. They contain cues about the conversation structure, the relationship among the participants and their roles in the discussion. These cues are hidden in vast files of text; by visualizing these archives, we can make them visible.
A conversation archives can be the foundation for an online community or a record of one's personal history. Having a way to easily make sense of this material can make it far more useful: it can become a tool for newcomers to comprehend the social environment, or for long-term participants to grasp the nuances of the evolving relationships.
There are many ways to visualize any dataset: the design of a visualization depends upon the questions one seeks to answer with it. A defense analyst may seek proscribed words or participants (Thomas and Cook 2006), while a discourse analyst may want to highlight disparities in usage (Sack 2005)[1]. In this case, the goal was to create a social visualization -- a depiction of social data for social use (Donath, Karahalios, and Viégas 1999; Donath 2002). Thus, we would like to know such things as: who participated? Who was active, influential, or helpful? What was talked about, and by whom? Was it a lively or desultory discussion?

[1] The conversation data used in this project was also depicted in (Abrams and Hall 2006) by Warren Sack as a dialectic map and by Mark Hansen as a word frequency graph.

Reading the full archive, and paying careful attention to the names associated with each entry, might allow one to answer these questions, but only with considerable effort and a high temporal cost. The visualization described in this paper, The Rhythm of Salience, was designed to create a quickly legible depiction of the conversation. The goal was to make a single image that would summarize the key social and semantic information in the archive, a map of the conversation.

Figure 1.   The Rhythm of Salience

Design Description

The Rhythm of Salience was commissioned by Janet Abrams and Peter Hall, as part of their book project Else/where Mapping (Abrams and Hall 2006). They invited six researchers to participate in online conversations with them on the topic of networks and mapping and then to visualize the resulting archive. The email conversation took place among the eight participants over a period of 22 days, during which a total of 30 messages were exchanged. The Rhythm of Salience is my depiction of this discussion.

Process and design

This visualization was created by hand, using Photoshop to arrange the archived text. The intent was to design a visualization that could potentially be generated automatically, but that was not constrained by current computational capabilities; i.e., there are clear rules that govern the display design, though some of these rules involve computationally complex analysis.
Several fundamental ideas guided this design. 1) Time and temporal rhythms are important (Venolia and Neustaedter 2003), for they provide a sense of the vitality of the conversation and the urgency with which different messages were received. 2) It is very useful to see who are the participants and their patterns of interaction(Donath, Karahalios, and Viégas 1999), for this is the basic social structure of the interaction. 3) The actual text should be incorporated into the visualization (Viégas, Golder, and Donath 2006). This both reveals useful patterns, such as terseness or verbosity, and allows the viewer to perceive as a unified whole the structure and content of the conversation.
The Rhythm of Salience shows this conversation as a single image, a grid where the x-axis has a column for each participant and the y-axis represents time, with the first day at the bottom. Each message is marked by a white square, located in the column of the author and at the time of its posting. Thin white lines run from message square to message square showing reply structure.
The full body text of each message is displayed, centered on the square that marks its place. Each participant's words and name are rendered in an individual color. Quotations within a message are shown in the color of the original author. Most of the text is rendered in a small font, but certain phrases are featured in larger letters. These are phrases that helped portray the individual participants; phrases both typical of and unique to that person.
This design makes is possible to quickly see the social patterns in the conversation, including the scale and temporal rhythm of the conversation, who are the most active participants, who is engaged with the others vs. expounding independently, who writes long missives vs. short notes. Reading the large highlighted words provides a gist of the conversation and a sense of the individuals' roles and direction. Although all the text is present on this image, one would not want to try to read the conversation in this format, for overlapping lines obscure the words. It is a depiction for seeing overall patterns, for getting the gist of the conversation, a sense of the participants.
In the particular conversation depicted for this commission, one can see, for example, that the conversation occurred mainly in two bursts, the first in response to Janet's initial posting, and the second, more than a week later, initiated by four short messages from Peter. This second part of the discussion was livelier, with more cross exchange and inter-quoting among the participants. We can see that this exchange was facilitated by Peter, whose multicolored postings are dappled with snippets from others. And we see that Marco was a relatively isolated participant, writing only two messages, with minimal quoting (and unquoted by others, probably because of their late arrival to the discussion).
From the featured words we get a sense of the participants as individuals. Peter and Janet, the hosts of the discussion, used phrases such as expand that for me, “common ground”, “please respond”, and “thanks for elaborating”, while the other six writers used phrases that showed their particular approaches to conversation mapping: “Multivariate”, “exploratory analysis”, “information retrieval” and “uncertainty” come from the words of Mark, a statistician, while “hegemonic control”, “agonistic pluralism”, “linguistic specificity” and “interlocutor”, are from Warren, a media theorist and linguist.

Future work: Automation

Many features in The Rhythm of Salience could be easily automated, including generating the basic grid, placing the white squares, drawing the reply lines and overlaying the text.
The most challenging feature to implement would be the phrase highlighting. The basic approach is to find phrases that occur with unusually frequency in a given text as compared with the expectation set by frequency in some larger base text. The base text can be the English language as a whole, or a more restricted set. This approach is used in Themail to visualize relationships within a user's personal archive of email (Viégas, Golder, and Donath 2006); it is the basis for Amazon.com's “Statistically Improbably Phrases” feature, which compares the phrases in one book with those found in all of that site's searchable books.
In doing the highlighting by hand, I was able to bring in much more semantic and contextual knowledge than these algorithms possess. Along with using unusualness as a metric for weighting, I also looked for a body of topically coherent words. For instance, "data" is not such are rare phrase, but in the context of Mark's other phrases, e.g. "multivariate","clusters", "features emerge", it gained salience as part of a cluster of mathematical, statistical and analytically oriented phrases. More challenging would be to automate the highlighting of phrases such as “please respond”, and “I'm interested” -- words that together illustrated Peter's role as conversation facilitator, but which are not particularly unusual phrases in the context of ordinary usage.
Automating the phrase highlighting that was done by hand is a linguistic analysis challenge, difficult but not impossible. Although not directly a problem in the field of visualization, it highlights this field's need for high-quality data and interpretation. A visualization that highlight the salient phrases in a text is useless if those phrases cannot be found.
Adding interactivity to the visualization would make it possible to differentiate among a larger number of participants and to make the full text easily readable. Our ability to differentiate among non-continguous colors is quite limited in the best of circumstances and in this application the available color palette is further reduced because the chosen colors must both render readable text and give equal weight to each participant. With an interactive interface, one could choose a participant to highlight and then see all instances where they are quoted by others. It would also be possible to pick individual messages and display them in an easily readable format.


There are an immense number of archived conversations. Congressional debates are in this form, as are private personal and corporate email lists. There are big public discussions on topics from celebrity sightings to nuclear disarmament. The utility of the archives depends upon the tools we have for viewing them. The Rhythm of Salience shows one way of depicting such conversations — a visualization that lets the viewer see in a single image a complex yet legible set of temporal, personal and semantic patterns that together create a portrait of the conversation.


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Sack, Warren. 2005. Discourse Architecture and Very Large-Scale Conversations. In Digital Formations, ed. Robert Latham and Saskia Sassen. Princeton, NJ: Princeton University Press/Social Science Research Council.
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Venolia, G. and C. Neustaedter. 2003. Understanding sequence and reply relationships within email conversations: A mixed-model visualization. MSR-TR-2002-102.
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